Routier Laura, Touati Sarah, Ghostine-Ramadan Ghida, Wallois Fabrice, Querne Laurent, Bourel-Ponchel Emilie
INSERM UMR 1105, Research Group on Multimodal Analysis of Brain Function, University of Picardie Jules Verne, Amiens, France.
Department of Pediatric Neurophysiology, Amiens-Picardie University Hospital, Amiens, France.
JAMA Netw Open. 2025 Jul 1;8(7):e2523029. doi: 10.1001/jamanetworkopen.2025.23029.
Predicting outcomes in preterm newborns is crucial for guiding therapeutic decisions and personalized rehabilitation. Prognostic models are a promising approach but rigorous validation is required to ensure their reliability and generalizability.
To provide external validation of the PRETERM-POM model, a multimodal prognostic model developed for predicting outcomes in extremely preterm newborns at age 2 years.
DESIGN, SETTING, AND PARTICIPANTS: In this prognostic study conducted at Amiens-Picardie University Hospital (France), the original parameters of the model, developed through multivariate analysis and decision-tree algorithms, were applied to a temporal validation group of preterm newborns born between January 2018 and January 2021 that did not overlap with the development population. The study included preterm newborns born at 23 to 28 weeks of gestational age who had undergone cranial ultrasound and conventional electroencephalogram within the first 14 days after delivery and follow-up until a corrected age of 2 years.
Neurodevelopment, assessed with the Denver Developmental Screening Test-II, was classified as favorable (no severe neurodevelopmental impairment [NDI]) or adverse (death or severe NDI). The area under the curve (AUC) for decision-tree classifications of adverse vs favorable outcomes was determined for the validation group and compared with the model development group using the DeLong test. Calibration and model fit were assessed using calibration-in-the-large, calibration curves, the Hosmer-Lemeshow test, and Brier score.
For the validation group (104 participants; median [IQR] gestational age at delivery, 26.3 [25.4-27.7] weeks; 46 [44.2%] male participants), the model achieved an AUC of 85.9% (95% CI, 79.0%-92.8%) for predicting outcomes, closely mirroring the performance observed in the development cohort. The model fit was good although it tended to underestimate the risk of adverse outcomes.
In this external validation study, the high performance of the model for predicting NDI in preterm newborns was confirmed. This multimodal approach, with a transparent display of risk factor contributions, enhances the potential of this model for clinical applications guiding timely management and decision-making.
预测早产儿的预后对于指导治疗决策和个性化康复至关重要。预后模型是一种很有前景的方法，但需要严格验证以确保其可靠性和可推广性。
对PRETERM - POM模型进行外部验证，该模型是一种多模态预后模型，用于预测极早产儿2岁时的预后。
设计、地点和参与者：在法国亚眠 - 皮卡第大学医院进行的这项预后研究中，通过多变量分析和决策树算法开发的模型原始参数应用于2018年1月至2021年1月出生的未与开发人群重叠的早产儿时间验证组。该研究纳入了孕23至28周出生的早产儿，他们在出生后前14天内接受了头颅超声和常规脑电图检查，并随访至矫正年龄2岁。
使用丹佛发育筛查测试 - II评估神经发育，分为良好（无严重神经发育障碍 [NDI]）或不良（死亡或严重NDI）。为验证组确定不良与良好结局的决策树分类的曲线下面积（AUC），并使用德龙检验与模型开发组进行比较。使用大样本校准、校准曲线、霍斯默 - 莱梅肖检验和布里尔评分评估校准和模型拟合。
对于验证组（104名参与者；分娩时中位 [IQR] 胎龄，26.3 [25.4 - 27.7] 周；46 [44.2%] 名男性参与者），该模型预测结局的AUC为85.9%（95% CI，79.0% - 92.8%），与在开发队列中观察到的表现相近。尽管该模型倾向于低估不良结局的风险，但模型拟合良好。
在这项外部验证研究中，证实了该模型在预测早产儿NDI方面的高性能。这种多模态方法，透明显示危险因素的贡献，增强了该模型在指导及时管理和决策的临床应用中的潜力。
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